Cloud data warehouse to
power your data-driven innovation
BigQuery is a serverless and cost-effective enterprise
data warehouse that works across clouds and scales with
your data. Use built-in ML/AI and BI for insights at
scale.
BigQuery Studio
provides a single, unified interface for all data
practitioners of various coding skills to simplify analytics
workflows from data ingestion and preparation to data
exploration and visualization to ML model creation and use.
It also allows you to use simple SQL to access Vertex AI
foundational models directly inside BigQuery for text
processing tasks, such as sentiment analysis, entity
extraction, and many more without having to deal with
specialized models.
Duet AI in BigQuery
An AI collaborator
integrated into BigQuery, Duet AI in BigQuery provides
contextual code assistance for writing SQL and Python. It
auto-suggests functions, code blocks, and fixes. With chat
assistance, you can use natural language to get real-time
guidance on performing specific tasks, reducing your need to
search for documentation. Learn more about
Duet AI in Google Cloud.
Flexibility, predictable
pricing, and best price performance
BigQuery editions
allow you to pick the right feature set for individual
workload requirements with the ability to mix and match for
the right price-performance. Compute capacity autoscaling
adds fine-grained compute resources in real time to match
the needs of your workload demands, and ensure you only pay
for the compute capacity you use. With compressed storage
pricing, you can reduce your storage costs while increasing
your data footprint at the same time.
BigQuery ML enables
data scientists and data analysts to build and
operationalize ML models on planet-scale structured,
semi-structured, and now unstructured data directly inside
BigQuery, using simple SQL—in a fraction of the time. Export
BigQuery ML models for online prediction into Vertex AI or
your own serving layer. Learn more about the
models we currently support.
BigQuery Omni is a
fully managed,
multicloud analytics
solution that allows for cost-effective and secure data
analysis across clouds and shares results within a single
pane of glass. Within BigQuery Analytics Hub, securely
exchange data assets
internally and across organizations and enhance analysis
with
commercial, public, and Google datasets.
Create and manage
data clean rooms
for privacy-centric measurement, data sharing, and
collaboration across organizations without moving or copying
data.
BigQuery has built-in
capabilities that ingest streaming data and make it
immediately available to query, along with native
integrations to streaming products, like
Dataflow.
Analyze large datasets interactively with BigQuery BI
Engine,
an in-memory analysis service
that offers sub-second query response time and high
concurrency. Accelerate query performance and reduce costs
within your environment
with BigQuery materialized views.
Query all data types
with BigQuery: structured, semi-structured, and
unstructured. Use BigLake to explore and
unify different data types
and build advanced models. Centrally discover, manage,
monitor, and govern data across
data lakes,
data warehouses, and data marts with consistent controls
with Dataplex, an
intelligent data fabric
that enables organizations to provide access to trusted
data.
Share insights with
built-in business intelligence
With built-in business
intelligence, create and share insights in a few clicks with
Looker Studio
or build data-rich experiences that go beyond BI with
Looker.
Analyze billions of rows of live BigQuery data in Google
Sheets with familiar tools, like pivot tables, charts, and
formulas, to easily derive insights from big data with
Connected Sheets.
BigQuery geospatial
uniquely combines the serverless architecture of BigQuery
with native support for geospatial analysis, so you can
augment your analytics workflows with location intelligence.
Simplify your analyses, see spatial data in fresh ways, and
unlock entirely new lines of business with support for
arbitrary points, lines, polygons, and multi-polygons in
common geospatial data formats.
Real-time change data
capture and replication
Synchronize data across
heterogeneous databases, storage systems, and applications
reliably and with minimal latency
with Datastream.
Datastream integrates with purpose-built and
extensible Dataflow templates to
pull change streams written to Cloud Storage, and create
up-to-date replicated tables in BigQuery for real-time
analytics.
How It Works
BigQuery's serverless architecture lets you use SQL
queries to analyze your data. You can store and
analyze your data within BigQuery or use BigQuery to
assess your data where it lives. To test how it works
for yourself, query data—without a credit card—using
the BigQuery sandbox.
Demo:
Solving business challenges with an end-to-end
analysis in BigQuery
Common Uses
Data warehouse migration
Migrate data
warehouses to BigQuery
Solve for today’s analytics
demands and seamlessly scale your business by
moving to Google Cloud’s enterprise data
warehouse. Streamline your migration path from
Netezza, Oracle, Redshift, Teradata, or Snowflake
to BigQuery using the free and fully managed
BigQuery Migration Service.
Make analytics easier by
bringing together data from multiple sources into
BigQuery. You can upload data files from local
sources, Google Drive, or Cloud Storage buckets,
use BigQuery Data Transfer Service (DTS), Cloud
Data Fusion plugins, replicate data from
relational databases with Datastream for BigQuery,
or leverage Google's industry-leading data
integration partnerships.
Gain a competitive advantage by
responding to business events in real time with
event-driven analysis. Built-in streaming
capabilities automatically ingest streaming data
and make it immediately available to query. This
allows you to stay agile and make business
decisions based on the freshest data. Or use
Dataflow to enable fast, simplified streaming data
pipelines for a comprehensive solution.
Predictive analytics can be
used to streamline operations, boost revenue, and
mitigate risk. BigQuery ML democratizes the use of
ML by empowering data analysts to build and run
models using existing business intelligence tools
and spreadsheets. Predictive analytics can guide
business decision-making across the organization.
Analyze and gain deeper insights
into your logging data with BigQuery. You can store,
explore, and run queries on generated data from
servers, sensors, and other devices simply using
GoogleSQL. Additionally, you can analyze log data
alongside the rest of your business data for broader
analysis all natively within BigQuery.
Increase
marketing ROI and performance with data and AI
Bring the power of Google AI to
your marketing data by unifying marketing and
business data sources in BigQuery. Get a holistic
view of the business, increase marketing ROI and
performance using more first-party data, and
deliver personalized and targeting marketing at
scale with ML/AI built-in. Share insights and
performance with Looker Studio or Connected
Sheets.
BigQuery data
clean rooms for privacy-centric data sharing
Create a low-trust environment
for you and your partners to collaborate without
copying or moving the underlying data right within
BigQuery. This allows you to perform
privacy-enhancing transformations in BigQuery SQL
interfaces and monitor usage to detect privacy
threats on shared data. Benefit from BigQuery
scale without needing to manage any infrastructure
and built-in BI and AI/ML.
From data ingestion to visualization, many partners have
integrated their data solutions with BigQuery. Listed above
are partner integrations through
Google Cloud Ready - BigQuery.
BigQuery is Google Cloud’s fully managed and
completely serverless enterprise data warehouse.
BigQuery supports all data types, works across
clouds, and has built-in machine learning and
business intelligence, all within a unified
platform.
An enterprise data warehouse is a system used for
the analysis and reporting of structured and
semi-structured data from multiple sources. Many
organizations are moving from traditional data
warehouses that are on-premises to cloud data
warehouses, which provide more cost savings,
scalability, and flexibility.
BigQuery offers robust security, governance, and
reliability controls that offer high availability
and a 99.99% uptime SLA. Your data is protected
with encryption by default and customer-managed
encryption keys.
There are a few ways to get started with
BigQuery. New customers get $300 in free credits
to spend on BigQuery. All customers get 10 GB
storage and up to 1 TB queries free per month, not
charged against their credits. You can get these
credits by signing up for the BigQuery free trial.
Not ready yet? You can use the
BigQuery sandbox
without a credit card to see how it works.
The
BigQuery sandbox
lets you try out BigQuery without a credit card.
You stay within BigQuery’s free tier
automatically, and you can use the sandbox to run
queries and analysis on public datasets to see how
it works. You can also bring your own data into
the BigQuery sandbox for analysis. There is an
option to upgrade to the free trial where new
customers get a $300 credit to try BigQuery.
Companies of all sizes use BigQuery to
consolidate siloed data into one location so you
can perform data analysis and get insights from
all of your business data. This allows companies
to make decisions in real time, streamline
business reporting, and incorporate machine
learning into data analysis to predict future
business opportunities.
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